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Expanded roles of leucine-responsive regulatory protein in
transcription regulation of the Escherichia coli genome:
Genomic SELEX screening of the regulation targets
Tomohiro Shimada,1,2,3 Natsumi Saito,4,5 Michihisa Maeda,6 Kan Tanaka1 and Akira Ishihama2,3
1
Chemical Resources Laboratory, Tokyo Institute of Technology, Nagatsuta, Yokohama, Japan
2
Department of Frontier Bioscience, Hosei University, Koganei, Tokyo, Japan
3
Research Center for Micro-Nano Technology, Hosei University, Koganei, Tokyo, Japan
4
Department of Chemistry and Material Engineering, Tsuruoka National College of Technology, Yamagata, Japan
5
Institute for Advanced Biosciences, Keio University, Yamagata, Japan
6
School of Agriculture, Meiji University, Kawasaki, Kanagawa, Japan
Correspondence: Tomohiro Shimada ([email protected])
DOI: 10.1099/mgen.0.000001
Leucine-responsive regulatory protein (Lrp) is a transcriptional regulator for the genes involved in transport, biosynthesis and
catabolism of amino acids in Escherichia coli. In order to identify the whole set of genes under the direct control of Lrp, we
performed Genomic SELEX screening and identified a total of 314 Lrp-binding sites on the E. coli genome. As a result, the
regulation target of Lrp was predicted to expand from the hitherto identified genes for amino acid metabolism to a set of
novel target genes for utilization of amino acids for protein synthesis, including tRNAs, aminoacyl-tRNA synthases and
rRNAs. Northern blot analysis indicated alteration of mRNA levels for at least some novel targets, including the aminoacyltRNA synthetase genes. Phenotype MicroArray of the lrp mutant indicated significant alteration in utilization of amino acids
and peptides, whilst metabolome analysis showed variations in the concentration of amino acids in the lrp mutant. From
these two datasets we realized a reverse correlation between amino acid levels and cell growth rate: fast-growing cells contain low-level amino acids, whilst a high level of amino acids exists in slow-growing cells. Taken together, we propose that
Lrp is a global regulator of transcription of a large number of the genes involved in not only amino acid transport and metabolism, but also amino acid utilization.
Keywords: Escherichia coli genome; Genomic SELEX; leucine response regulator; regulation target; transcription factor.
Abbreviations: CE, capillary electrophoresis; ESI, electrospray ionization; Lrp, leucine-responsive regulatory protein; PM,
Phenotype MicroArray; RNAP, RNA polymerase; TOF, time-of-flight.
Data statement: All supporting data, code and protocols have been provided within the article or through supplementary
data files. Three supplementary tables are available with the online Supplementary Material.
Introduction
Leucine-responsive regulatory protein (Lrp) belongs to the
widely distributed Lrp–AsnC family of small, basic transcription factors. Escherichia coli Lrp of 164 aa in size consists
of three functional domains: an N-terminal 40% domain
Received 15 April 2015; Accepted 26 May 2015
containing the helix–turn–helix motif of DNA binding, the
next 40% of the middle domain responsible for transcription activation and an overlapping C-terminal domain
required for the response to Leu (de los Rios & Perona,
2007; Ettema et al., 2002; Platko & Calvo, 1993). Lrp forms
a dimer in solution (Calvo & Matthews, 1994; Willins
et al., 1991), but self-assembles to form a mixture of octamers and hexadecamers (Chen et al., 2001b). As Lrp-regu-
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1
T. Shimada and others
lated promoters commonly contain multiple adjacent Lrpbinding sites, the higher-order structures could play an
important functional role.
Lrp was first identified in E. coli as a regulatory protein
involved in the control of the transport of branchedchain amino acids (Anderson et al., 1976). Subsequently,
mutations in the lrp gene were found to influence the
expression of operons involved in the biosynthesis and
degradation of some more amino acids (Lin et al., 1992;
Platko et al., 1993), suggesting that Lrp plays a regulatory
role in transport and metabolism of not only Leu, but
also some other amino acids. The number of regulation
targets of Lrp has further increased concomitant with the
advance of genome expression monitoring systems. Proteome analysis suggested the alteration of levels of a total
of 25 proteins in the lrp mutant (Ernsting et al., 1992).
The alteration of expression levels of up to 85 proteins
was also identified by random phage insertions into the
genome (Lin et al., 1992). The transcriptome analysis indicated that as many as w400 genes or *10% of the genes
within the E. coli genome are affected in the absence of Lrp,
of which at least 130 were suggested to be under the direct
control of Lrp (Cho et al., 2008; Hung et al., 2002; Tani
et al., 2002). A certain proportion of the regulated genes
are involved, as originally proposed, in transport and
metabolism of amino acids, but Lrp has also been
suggested to regulate genes involved in biosynthesis and
degradation of various metabolites other than amino
acids (Brinkman et al., 2003; Calvo & Matthews, 1994;
Newman & Lin, 1995). In addition, the genes for other cellular functions, such as pili synthesis and adhesion to host
cells, have been indicated to be under the control of Lrp
(Calvo & Matthews, 1994). Furthermore, Lrp is also
known to function as a structural element, together with
other the nucleoid proteins, to establish the conformation
of genome DNA (reviewed by Ishihama, 2009). Thus, as in
the case of other nucleoid proteins, Lrp is a bifunctional
protein, playing a regulatory role in gene expression and
an architectural role in nucleoid organization. Accordingly,
the intracellular level of Lrp in exponentially growing
E. coli cells is as abundant as other nucleoid proteins (Ali
Azam et al., 1999; Ishihama et al., 2014; Willins et al.,
1991).
One unique characteristic of Lrp is its functional modulation
after interaction with multiple effectors. The regulatory function of Lrp was first recognized under the control of Leu
(Chen & Calvo, 2002; Chen et al., 2001a; Haney et al.,
1992; Platko & Calvo, 1993; Roesch & Blomfield, 1998; Willins et al., 1991). Leu is the most abundant building block
(*9% of total blocks) of all proteins in E. coli, suitable as
a representative signal molecule of the availability of substrates for protein production. Lrp acts as a sensor of this
key signal, leading to modulation of its activity and specificity. The effector Leu modulates multimerization of Lrp
and thereby controls the transcription of certain target
genes (Chen & Calvo, 2002; Chen et al., 2001a, b). In most
cases, Lrp has been reported to activate the operons that
2
Impact Statement
Leucine-responsive regulatory protein (Lrp) is
known as a global regulator of the genes for transport, biosynthesis and catabolism of amino acids to
establish their balance needed for protein synthesis.
After Genomic SELEX screening, however, we identified that Lrp not only controls the production of
amino acids, but also the utilization pathway of
amino acids by regulating the genes for tRNAs, aminoacyl-tRNA synthetases and rRNAs. Phenotype
MicroArray and metabolome analyses indicated
Lrp-mediated correlation between the intracellular
levels of amino acids and their utilization for protein
synthesis: the intracellular levels are low for amino
acids that are efficiently used for protein synthesis,
allowing fast cell growth, but cell growth is low
even in the presence of high levels of amino acids
that are not so much used for protein synthesis.
Here, we also identified another expanded role of
Lrp in regulation of a set of transcription factors,
each playing a regulatory role in the control of
a specific metabolism pathway or physiological
response to a specific nutritional condition. Lrp
stays on the top of this hierarchic network of transcription factors. Overall, we propose an expanded
role for Lrp in controlling the production and utilization of amino acids – the key metabolites of cell
construction.
encode enzymes for amino acid biosynthesis and repress
the operons that encode catabolic enzymes (Calvo &
Matthews, 1994). The activation of some operons is overcome by Leu, but in other cases the activation requires Leu
(Calvo & Matthews, 1994; Ernsting et al., 1992; Lin et al.,
1992; Newman et al., 1992). A group of regulation target
genes are, however, activated by Lrp independent of Leu.
More complexity has arisen from the findings that amino
acids other than Leu are involved in the regulation of activity
and specificity of Lrp. In place of Leu, Ala has been indicated
to act as an effector of Lrp (Berthiaume et al., 2004; Kim
et al., 2010; Martin, 1996; Zhi et al., 1998, 1999).
A systematic survey of effector function for all amino acids
indicated that His, Ile, Met and Thr influence, besides Leu
and Ala, Lrp activity (Hart & Blumenthal, 2011). The direction and level of the influence on Lrp activity by each amino
acid effector appears variable depending on the target genes
and under the culture conditions. The complex nature of
Lrp action may be related to its physiological role to harmonize the expression of Lrp regulon genes to match with the
surrounding conditions, such as the composition and availability of nutrients.
As a short-cut approach to identify the whole set of regulation target genes of the RNA polymerase (RNAP) sigma
subunits and a total of *300 species of transcription
factors, we developed the Genomic SELEX screening
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Microbial Genomics
Expanded roles of Lrp in transcription regulation
system in vitro (Shimada et al., 2005). By using this SELEX
system, we succeeded in identifying the whole set of constitutive promoters that are recognized by the RNAP RpoD
holoenzyme alone in the absence of supporting transcription factors (Shimada et al., 2014). The functional modulation of RNAP after replacement of sigma factors was
then identified by the same SELEX system (T. Shimada
and A. Ishihama, in preparation). Along this line, a systematic search of regulation targets by the SELEX system
is in progress for *300 species of E. coli transcription factors. In this study, an attempt was made to identify the
regulation target genes that are recognized by Lrp alone
in the absence of any effectors. The results herein described
indicate a novel role of Lrp in the regulation of a large
group of genes involved in not only the transport and
metabolism of amino acids, but also the polymerization
of amino acids into proteins.
Methods
Bacterial strains and plasmids. E. coli DH5a was
used for plasmid amplification. E. coli BL21 was used for
Lrp expression. E. coli BW25113 (W3110 lacI q rrnBT14
DlacZWJ16 hsdR514 DaraBADAH33 DrhaBADLD78)
(Datsenko & Wanner, 2000) and JW0872 (a lrp singlegene deletion mutant of BW25113) (Baba et al., 2006)
were obtained from the E. coli Stock Center (National
Bio-Resource Center, Mishima, Japan). Cells were grown
in M9/glucose medium at 30 uC under aeration with
constant shaking at 150 r.p.m. Cell growth was monitored
by measuring OD600.
Expression and purification of Lrp. Expression plasmid
pLrp of Lrp protein was constructed essentially according
to the standard procedure in this laboratory (Shimada
et al., 2005; Yamamoto et al., 2005). The Lrp-coding
sequence of E. coli K-12 W3110 was PCR-amplified and
inserted into pET21a between Nde I and Not I so as to
fuse to the C-terminal His-tag. The expression of Histagged Lrp was performed in E. coli BL21. Lrp was
affinity-purified according to the standard procedure
(Shimada et al., 2005; Yamamoto et al., 2005).
Preparation of antibodies. Antibodies against Lrp were
produced in two rabbits by injecting purified Lrp protein
(Ishihama et al., 2014). After examination of antibody
activity using immunoblot analysis, the batch of higher
activity was used in this study. Antibody production was
performed in the Animal Laboratory of Mitsubishi
Chemical Medience under the guidelines for animal
experiments of the Ministry of Education, Culture,
Sports, Science and Technology of Japan.
Genomic
SELEX
screening
of
Lrp-binding
sequences. The Genomic SELEX method was carried
out as described previously (Shimada et al., 2005).
A mixture of DNA fragments of the E. coli K-12 W3110
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genome was prepared after sonication of purified genome
DNA and cloned into a multi-copy plasmid pBR322.
In each SELEX screening, the DNA mixture was
regenerated by PCR. For SELEX screening, 5 pmol of the
mixture of DNA fragments and 10 pmol purified Lrp
were mixed in a binding buffer (10 mM Tris/HCl, pH
7.8 at 4 uC, 3 mM magnesium acetate, 150 mM NaCl
and 1.25 mg BSA ml21) and incubated for 30 min at
37 uC. The DNA–Lrp mixture was treated with anti-Lrp
antibody, and DNA fragments recovered from the
complexes were PCR-amplified and subjected to next
cycle of SELEX for enrichment of Lrp-bound DNA
fragments.
For SELEX-chip analysis, DNA samples were isolated from
the DNA–protein complexes at the final state of SELEX,
PCR-amplified and labelled with Cy5, whilst the original
DNA library was labelled with Cy3. The fluorescently
labelled DNA mixtures were hybridized to a DNA microarray consisting of 43 450 species of 60 bp DNA probes,
which were designed to cover the entire E. coli genome at
105 bp interval (Oxford Gene Technology) (Shimada
et al., 2005, 2008). Fluctuation level of the fluorescent
intensity between the 43 450 probes was less than
twofold for the original DNA library. The fluorescence
intensity of each peak of the test sample was then
normalized with that of the corresponding peak of the
original library. After normalization of each pattern, the
Cy5/Cy3 ratio was measured and plotted along the E. coli
genome.
Extraction of metabolites. Samples for intracellular
metabolite measurements were processed as described
previously (Ohashi et al., 2008; Soga et al., 2003). The
exponential-phase culture (OD600 0.5) was filtered under
vacuum through a 0.4 mm pore size filter. Cells on the
membrane filter were immediately washed with MilliQ
water to remove extracellular components and then
quickly immersed in 2 ml methanol containing 2.5 mM
each of the internal standards, methionine sulfone, MES
and D -camphor 10-sulfonic acid. Dishes containing filters
were sonicated for 30 s to resuspend the cells. A 1.6 ml
aliquot of the cell suspension was transferred to a tube,
and mixed with 1.6 ml chloroform and 0.64 ml MilliQ
water. After vortexing and centrifugation, the aqueous
layer was recovered and clarified using Ultrafree-MC
ultrafilter
devices
for
Metabolome
Analysis
UFC3LCCNB-HMT (Millipore). After drying up,
materials attached on the filter were dissolved in 25 ml
MilliQ water and subjected to capillary electrophoresis
time-of-flight MS (CE-TOF-MS) analysis.
Instrumentation
and
CE-TOF-MS
conditions.
CE-TOF-MS analysis was carried out using an Agilent
CE system equipped with an Agilent 6210 TOF mass
spectrometer, Agilent 1100 isocratic HPLC pump,
Agilent G1603A CE-MS adaptor kit and Agilent G1607A
CE-ESI (electrospray ionization)-MS sprayer kit
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T. Shimada and others
(Agilent Technologies). The system was controlled by
Agilent G2201AA ChemStation software for CE. Data
acquisition was performed by Analyst QS 7222 software
for Agilent TOF (Applied Biosystems and MDSSciex).
Instrumental conditions for separations and detections of
metabolites were as follows. The cationic metabolites
were separated on a fused silica capillary (50 mm|100
cm) using 1 M formic acid as the electrolyte with the
voltage set at 30 kV. A solution of 50% (v/v) methanol/
water was delivered as the sheath liquid at a flow rate of
10 ml min21 (Soga & Heiger, 2000; Soga et al., 2003).
Separations of anionic metabolites and nucleotides were
carried out on a COSMO(+)Capillary (Nacalai Tesque)
using 50 mM ammonium acetate (pH 8.5) as the
electrolyte. The applied voltage was set at 230 kV.
A solution of 5 mM ammonium acetate in 50% (v/v)
methanol/water was delivered as the sheath liquid (Soga
et al., 2002; 2003). ESI-TOF-MS was conducted in the
positive-ion mode (4000 V) for cationic metabolites, and
the negative-ion mode (3500 V) for anionic metabolites
and nucleotides. Dry nitrogen gas was maintained at 10
p.s.i. Exact mass data were acquired over a 50–1000 m/z
range (Ohashi et al., 2008; Soga et al., 2006). The raw
data obtained using CE-TOF-MS were processed with
a proprietary software program, MasterHands, that
provided noise-filtering, peak detection and integration of
the peaks from sliced electropherograms and alignment of
the migration time (Sugimoto et al., 2010). Absolute
quantification was performed using metabolite standards
for calibration. Under the conditions employed, the
deviation of metabolite levels was v10% (Soga et al., 2006).
Phenotype MicroArray (PM) for the growth test. The
PM assay was performed essentially according to the
published methods (Bochner et al., 2001; Zhou et al.,
2003) using Biolog PM plates (Biolog). E. coli BW25113
and JW0872 were grown overnight at 30 uC in M9/
glucose (0.2%). Cells were washed with IF-0 (inoculating
fluid), and then resuspended in IF-0 for PM plates 1 and
2, in IF-0 containing 20 mM sodium succinate and
2 mM ferric citrate for PM plates 3–8, and in IF-10
containing 2.0 g tryptone, 1.0 g yeast extract and 1.0 g
NaCl l–1 at a density corresponding to 85% transmittance (OD420*0.12) using a 20 mm diameter tube.
Tetrazolium violet was added at the final concentration
of 0.01%. The suspensions were then inoculated into the
appropriate microplates PM1–10 for bacteria (Biolog) at
a volume of 0.1 ml per well. The microplates were placed
in an OmniLog instrument at 30 uC and monitored by
OmniLog reader (Biolog) for colour change in the wells
at 15 min intervals up to 72 h. Kinetic data were analysed
with OmniLog-PM software. Each strain was tested at
least twice.
Northern blot analysis. Total RNAs were extracted
from exponentially growing E. coli cells (OD600 0.5) by
the hot phenol method. RNA purity was checked by
electrophoresis on 1.5% agarose gel in the presence of
4
formaldehyde followed by staining with methylene blue.
Northern blot analysis was performed essentially as
described previously (Shimada et al., 2007, 2011). DIGlabelled probes were prepared by PCR amplification using
W3110 genomic DNA (50 ng) as template, DIG-11-dUTP
(Roche) and dNTP as substrates, gene-specific forward
and reverse primers, and Ex Taq DNA polymerase
(TaKaRa). Total RNAs (1 mg) were incubated in
formaldehyde-MOPS gel-loading buffer for 10 min at
65 uC for denaturation, subjected to electrophoresis on
formaldehyde-containing 1.5% agarose gel and then
transferred to a nylon membrane (Roche). Hybridization
was performed with a DIG easy Hyb system (Roche) at
50 uC overnight with a DIG-labelled probe. For detection
of the DIG-labelled probe, the membrane was treated with
anti-DIG-AP Fab fragments and CDP-Star (Roche), and
the image was scanned with a LAS-4000 IR multi-colour
imager (Fuji Film).
Results
Search for Lrp-binding sequences by Genomic
SELEX screening
In order to identify the whole set of target promoters,
genes and operons under the direct control of Lrp, we performed Genomic SELEX screening (Shimada et al., 2005),
in which purified His-tagged Lrp was mixed with a collection of E. coli genome fragments of 200–300 bp in length
and Lrp-bound DNA fragments were affinity-isolated.
As the specificity of target recognition of Lrp is known
to change toward different directions, depending on the
species of interacting amino acid effector (Hart &
Blumenthal, 2011), in this study we carried out SELEX
screening using 0.1 mM Lrp alone in the absence of effectors. Under these conditions, Lrp exists mainly in the
monomer state as estimated from the known association
constants, but a possible influence of the C-terminal
His-tag addition on its multimerization is not ruled out.
The list of DNA sequences thus identified should provide
the basic set of regulation targets by Lrp alone. The original
mixture of genomic DNA fragments formed smear bands
on PAGE, but after two cycles of Genomic SELEX, DNA
fragments with high affinity to Lrp were enriched, forming
sharper bands on PAGE gels (data not shown). As a shortcut approach to identify the whole set of sequences recognized by Lrp, we subjected this isolated SELEX fragment
mixture to DNA chip analysis using an E. coli tilling
array (Shimada et al., 2008, 2011). In brief, the SELEX
DNA fragments were labelled with Cy5 whilst the original
DNA library was labelled with Cy3. The mixtures were then
hybridized with the DNA tilling microarray (Oxford Gene
Technology) and the fluorescence intensities bound on
each probe were measured. For identification of Lrp-binding sites, the Cy5/Cy3 ratio was plotted along a total of
43 450 probes aligned on the array in the order of the
E. coli genome (Fig. 1).
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Microbial Genomics
Expanded roles of Lrp in transcription regulation
700
amiC/argA
–/ilvI
–/hchA
600
–/yeeN
Lrp-binding intensity
ycgB/dadA
500
–/brnQ
yciZ/–
artP/–
insH/slp
livJ/–
–/sdaC
dppA/–
–/cycA
lrhA/alaA
400
300
200
100
0
0
500000
1000000
1500000
2000000
2500000
3000000
3500000
4000000
4500000
Genome position (bp)
Fig. 1. Lrp-binding sites on the E. coli K-12 genome identified by SELEX-chip. After two cycles of Genomic SELEX screening, a collection of Lrp-bound DNA fragments was subjected to SELEX-chip analysis using the tilling array of the E. coli K-12 genome (for details, see
Methods). The y-axis represents the relative number of Lrp-bound DNA fragments, whereas the x-axis represents the position on the
E. coli genome. The regulation targets were predicted based on the location of Lrp-binding sites. For Lrp sites within type A spacers, both
of the flanking genes of the bidirectional transcription units are shown. For Lrp sites within type B spacers, only the genes located downstream of the Lrp sites are shown, but the genes on the other side are shown as a minus symbol. Details of target genes are listed in
Table S1.
By setting a cut-off level of the Genomic SELEX pattern at
10 (Fig. 1), a total of 314 Lrp-binding peaks were identified, of which 228 (72%) were within intergenic spacers
and 86 (28%) were inside ORF regions (Table 1). The
Lrp-binding spacers could be classified into three groups:
type A, spacers between bidirectional transcription units
(78 spacers); type B, spacers upstream of one transcription
unit, but downstream of another transcription unit (140
spacers); and type C (10 spacers), spacers downstream of
both transcription units (Table 1). In the case of type A
spacers, Lrp might regulate one or both of the transcription
units, whilst Lrp bound within type B spacers should be
involved in regulation of one-directional transcription.
Up to the present time, we have performed SELEX-chip
screening for w150 E. coli transcription factors (for a
review, see Ishihama, 2012); some, but not always,
showed binding within type C spacers, implying an asyet unidentified regulatory role for this group of transcription factor binding. Likewise, the total of 86 Lrp-binding
sites inside ORFs may play certain regulatory roles because
the amount of transcription factor-binding sites inside
ORFs varies depending on transcription factor species
(Ishihama, 2012; Shimada et al., 2008).
Prediction of the regulation targets of Lrp
In prokaryotes, transcription factors generally bind near
the promoter for effective interaction with promoter-
Table 1. SELEX-chip screening of Lrp-binding sequences: Lrp-binding sites on the E. coli genome
A total of 314 Lrp-binding sites can be classified into three groups: type A, spacers between bidirectional transcription units (78 spacers); type B,
spacers upstream of one transcription unit but downstream of another transcription unit (140 spacers); and type C (10 spacers), spacers downstream of both transcription units.
Location
Within type A spacers
Within type B spacers
Within type C spacers
Inside ORFs
http://mgen.sgmjournals.org
No. Lrp sites
No. targets
RegulonDB
ChIP-chip
78
140
10
86
314
78–156
140
0
(89)
218–296
9
15
0
0
24
32
55
0
0
87
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T. Shimada and others
bound RNA polymerase, and thus the target genes and
promoters under the control of Lrp could be estimated
based for the Lrp-binding sites within type A and type B
spacers. Based on the location of Lrp-binding sites on the
E. coli genome, we then predicted the set of regulation
target genes and operons recognized by Lrp alone. The
total number of Lrp regulation targets thus estimated
ranged between a minimum of 218 (type A 78 plus type B
140) and a maximum of 296 (type A 156 plus type B 140)
(Table 1; for details see Table S1, available in the online Supplementary Material). The total number of regulation targets
of Lrp has been estimated to be *130 based on ChIP-chip
analysis (Cho et al., 2008) whilst the number of Lrp targets
listed in RegulonDB is 43 (Salgado et al., 2006). The list of
regulation targets predicted based on the SELEX screening
covered 87 (67%) of ChIP-chip data and 24 (60%) of the
RegulonDB list (Table 1). In order to avoid background
noise, we set a rather high cut-off level at 10 (see Fig. 1)
and, as a result, we failed to pick up some of the known targets, of which most could be recovered by setting the cut-off
level at 3.0 (data not shown).
The total number of Lrp targets increased *2.3-fold from
130 up to 296. The marked increase in the number of regulation targets has been identified for not only Lrp, but also
most of the transcription factors so far examined by SELEX
screening (Ishihama, 2010, 2012; Shimada et al., 2011).
This increase was mainly attributable to the difference
between in vitro estimation by SELEX and in vivo measurement by ChIP-chip. The binding in vivo of Lrp should be
interfered by competitive binding by other DNA-binding
proteins. In addition, the intracellular conditions were
different from in vitro SELEX conditions, altogether influencing the Lrp–DNA interaction modes. Amongst the total
of 296 candidate genes under the direct control of Lrp, 114
were related to the metabolism of amino acids (Table 3,
type A plus type B lane). This value corresponded to
89% of the hitherto identified genes involved in the synthesis and degradation of amino acids, in good agreement
with the predicted regulatory functions of Lrp. A total of
261 transporter genes, including 43 transporters of amino
acids, are listed in Genobase. After SELEX screening, a
total of 84 transporter genes were found to be under the
direct control of Lrp (Table 3, type A plus type B lane),
of which 35 represented the genes for amino acid transporters (80% of total amino acid transporters) (Table 2).
Search for the regulatory roles of Lrp: PM
After Genomic SELEX screening, we recognized a sudden
and marked increase in the list of regulation targets of
Lrp, indicating that Lrp plays as-yet unidentified regulatory
roles in overall transcription of the E. coli genome. As an
attempt to obtain insights into the regulatory role of Lrp,
we performed a PM assay, which allows the detection of
cell growth under a total of 960 culture conditions: the presence of 192 species of carbon source (PM plates 1 and 2),
96 species of nitrogen source (PM plate 3), 96 species of
phosphorus and sulfur sources (PM plate 4), 96 species
of nutrient supplement (PM plate 5), 288 chemicals as
peptide nitrogen source (PM plates 6–8), 96 species of
osmolyte (PM plate 9) and 96 different pH conditions
(PM plate 10) (Bochner, 2009). We measured the growth
of WT E. coli BW25113 and JW0872 (lrp single-gene deletion mutant of BW25113). The time-course of cell
growth was monitored by measuring the cell densitydependent increase in respiration (Bochner et al., 2001).
After 3 days of culture, the difference of growth between
the WT and the lrp mutant was estimated by comparison
of the growth curves (Fig. 2). Growth rates of the WT
and lrp mutant were essentially the same in the absence
of any additions (see microplate well 1 for each PM plate).
The lrp mutant strain exhibited slower growth under a
total of 59 conditions, of which 50 were in the presence
of specific nitrogen sources, four in the presence of specific
carbon sources, four in the presence of nutrient supplement and one at specific pH (marked in green for representative compounds in Fig. 2). It is noteworthy that the
lrp mutant showed significantly reduced growth especially
in the presence of Ala, Cys, Gly, Ser and Trp as a sole nitrogen source (Fig. 2, PM plate 3; for details, see Table S2) and
some peptides such as Ala–Gly, Ala–Leu, Gly–Asn, Ala–His
and Ala–Thr, each including one of these five amino acids
Table 2. SELEX-chip screening of Lrp-binding sequences: Lrp regulon genes involved in transport and metabolism of amino acids
The Lrp regulon genes involved in transport and metabolism of amino acids, tRNA, tRNA charging and rRNA are listed. The number of the whole
set of genes involved in those functions is shown in Whole set column. The number of genes identified by SELEX screening is shown in the SELEXchip column. The number of genes listed in RegulonDB (Salgado et al., 2006) or ChIP-chip analysis (Cho et al., 2008) is shown in the DB+ChIPchip columns. Percentage shows the coverage of the whole set of genes.
Function
Transporter
Metabolism
tRNA
tRNA charging
rRNA
6
Whole set
43
128
85
24
21
SELEX-chip (%)
35
114
17
6
9
(81)
(89)
(20)
(25)
(43)
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DB+ChIP-chip (%)
24 (56)
41 (32)
10 (12)
1 (4)
21 (100)
Microbial Genomics
A total of 314 Lrp-binding sites were identified within spacers on the entire E. coli K-12 W3110 genome. A total of 78 Lrp-binding sites were identified within type A spacers, which direct bidirectional transcription. A total of 140 Lrp-binding sites were located within type B spacers upstream of one-side genes and downstream of another-side genes. Based on the gene orientation around
these binding sites, the genes and operons under the control of Lrp were estimated. Lrp-binding sites listed in RegulonDB (Salgado et al., 2006) or ChIP-chip analysis (Cho et al., 2008) are shown
in the DB or ChIP-chip columns. Genes encoding amino acid metabolism, translation apparatus, transporters and transcription factors are shown in AA, TR, TP and TF columns, respectively.
Type-A spacers
7
Position
Operon
Gene
Direction
42168
83830
255832
310970
400468
584962
632754
651072
655436
675858
784656
815960
823832
865772
915432
931532
1091836
1197570
1236636
1271162
1297734
1328732
1406036
1554532
1676134
1719066
1732246
1744232
1785460
1830358
1977470
1984252
1987632
2036832
caiTABCDE
leuLABCD
pepD
matA
ddlA
ompT
ydbH–ynbE–ydbL
citCDEFXG
dcuC
ybeQ
ybgS
ybhK
ybhPON
moeAB
aqpZ
trxB
pgaABCD
ymfED
ycgB
chaA
adhE
yciN
ydaM
bdm–sra
pntAB
slyA
grxD
ydhQ
ppsA
astCADBE
insA
araFGH
yecH
yedWV
caiT
leuL
pepD
matA
ddlA
ompT
ybdH
citC
dcuC
ybeQ
ybgS
ybhK
ybhP
moeA
aqpZ
trxB
pgaA
ymfE
ycgB
chaA
adhE
yciN
ydaM
bdm
pntA
slyA
grxD
ydhQ
ppsA
astC
insA
araF
yecH
yedW
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
Lrp
DB
Direction
Gene
Operon
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
fixA
leuO
gpt
ykgL
iraP
pauD
ybdL
dpiB
pagP
ybeR
aroG
moaA
ybhQ
iaaA
ybjD
lrp
ycdT
lit
dadA
chaB
ychE
topA
ydaN
osmC
ydgH
ydhI
ydhO
valV
ppsR
xthA
uspC
ftnB
tyrP
yedX
fixABCX
leuO
gpt
ykgL
iraP
pauD
ybdL
dpiBA
pagP
ybeR–djlB
aroG
moaABCDE
ybhQ
iaaA–gsiABCD
ybjD
lrp
ycdT
lit
dadAX
chaBC
ychE
topA
ydaN
osmC
ydgH
ydhIJK
ydhO
valVW
ppsR
xthA
uspC
ftnB
tyrP
yedX
Intensity
16.4
351.5
10.8
53.5
11.2
233.7
10.8
28.2
19.8
32.7
264.1
142.3
42.9
29.0
32.5
117.1
13.0
13.5
453.6
25.1
121.2
27.2
38.1
16.0
182.2
251.5
11.6
30.5
65.9
358.3
22.0
24.9
66.6
11.7
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L
ChIP
R
L
R
AA
L
TR
R
L
TP
R
L
TF
R
L
R
Expanded roles of Lrp in transcription regulation
http://mgen.sgmjournals.org
Table 3. Lrp-binding sites on the E. coli genome
Type-A spacers
Microbial Genomics
Position
Operon
Gene
Direction
2066864
2166740
2220130
2301638
insH
yegRZ
bglX
napFDAGHBC–
ccmABCDEFGH
ais
lrhA
yfcZ
xapAB
aegA
ileY
stpA
cas3
amiC
yqeF
yqeK
yqgD
ygiW
aer
tdcABCDEFG
yhcC
nanR
envR
fkpA
yhgE
livKHMGF
yhiL
insH
gadW
yhjR
xylAB
bax
gltS
yieP–hsrA
yihG
yihA
sthA
yjbS
aspA–dcuA
frdABCD
insH
yegR
bglX
napF
ais
lrhA
yfcZ
xapA
aegA
ileY
stpA
cas3
amiC
yqeF
yqeK
yqgD
ygiW
aer
tdcA
yhcC
nanR
envR
fkpA
yhgE
livK
yhiL
insH
gadW
yhjR
xylA
bax
gltS
yieP
yihG
yihA
sthA
yjbS
aspA
frdA
2363870
2405468
2459060
2523166
2583742
2784156
2796840
2885230
2947130
2983838
2989270
3084748
3167858
3217358
3265368
3352352
3372648
3411666
3475464
3530664
3595854
3632570
3651640
3662638
3694242
3729066
3735330
3826772
3939530
4044850
4048966
4158946
4267330
4366438
4380356
Lrp
DB
Direction
Gene
Operon
,
,
,
,
.
.
.
.
yoeA
yegS
dld
yojO
yoeA
yegS
dld
yojO
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
arnB
alaA
fadL
yfeN
narQ
ygaQ
ygaW
sokX
argA
yqeG
ygeG
metK
qseB
ygjG
tdcR
gltB
dcuD
acrE
slyX
pck
yhhK
yhiM
slp
gadY
bcsE
xylF
malS
xanP
rrsC
polA
csrC
fabR
aphA
fxsA
poxA
arnBCADTEF
alaA
fadL
yfeN
narQ
ygaQ
ygaW
sokX
argA
yqeG
ygeG
metK
qseBC
ygjG
tdcR
gltBDF
dcuD
acrEF
slyX
pck
yhhK
yhiM
slp–dctR
gadY
bcsEFG
xylFGHR
malS
xanP
rrsC–gltU–rrlC–rrfC
polA
csrC
fabR–yijD
aphA
fxsA
poxA
Intensity
49.2
14.9
11.7
11.4
22.0
384.3
177.1
286.8
18.2
30.6
147.4
10.6
630.0
44.9
144.7
72.0
25.2
102.6
27.7
319.6
26.0
16.5
11.0
25.7
277.3
60.4
552.8
86.3
39.8
16.1
37.0
16.8
17.7
66.4
23.4
23.7
266.0
61.5
10.2
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L
ChIP
R
L
R
AA
L
TR
R
L
TP
R
L
TF
R
L
R
T. Shimada and others
8
Table 3. cont.
Type-A spacers
Position
4437446
4440430
4501960
4554598
4633450
Operon
Gene
Direction
ytfJ
msrA
insG
yjiC
rob
ytfJ
msrA
insG
yjiC
rob
,
,
,
,
,
142 genes
78
Lrp
DB
Direction
Gene
Operon
Intensity
.
.
.
.
.
ytfK
ytfM
yjhB
iraD
creA
ytfK
ytfMNP
yjhBC
iraD
creABCD
109.6
95.6
27.5
62.9
57.6
78
122 genes
Operon
Gene
AA gene
L
9262
85536
152844
155442
236848
251970
317836
320346
389160
418534
433872
467530
479234
530448
536860
567532
569664
603938
659532
696540
9
735642
736068
802538
837438
892742
903170
Operon
yadMLKC
htrE
rclCB
hemB
aceB
ybbB
mscM
lipA
metT–leuW–glnUW–
metU–glnVX
ybiJ
artPIQM
R
L
9
19
19
Type-B spacers
Position
ChIP
Direction Lrp Direction Gene
Operon
talB
leuO
yadM
htrE
dnaQ
dinB
rclC
ykgD
hemB
phoR
ribD
.
.
,
,
.
.
,
.
,
.
.
.
.
,
,
.
.
,
.
,
.
.
mog
ilvI
htrE
ecpD
aspV
yafN
ykgC
ykgE
insF
brnQ
ribE
mog
ilvIH
cof
aceB
ybbB
glxR
insF
ybcK
mscM
lipA
metT
.
,
,
.
.
.
,
,
,
.
,
,
.
.
.
,
,
,
ybaO
hha
allS
ybbW
emrE
ybcL
nfsB
ybeF
asnB
ybfC
ybfQ
ybhI
ybiJ
ybjN
artP
.
.
.
,
.
,
.
.
.
,
.
,
ybfQ
ybfL
ybhJ
ybiI
potF
ybjP
aspV
yafNOP
ykgEFG
brnQ–proY
ribE–nusB–
thiL–pgpA
ybaO
ybbW–allB–ybbY–glxK
emrE
ybcLM
ybfQ
ybfL
ybhJ
potFGHI
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Intensity L
40.6
553.6
15.6
192.8
50.4
14.6
75.5
61.5
25.6
319.3
31.3
17.3
25.4
10.4
33.3
18.1
123.3
10.2
13.5
132.6
69.4
151.6
17.3
128.4
166.5
330.3
R
L
32
73
70
DB
Gene
AA
TR
R
20
46
46
ChIP
R L
L
TP
R
4
8
8
AA
R L
L
TF
R
L
13
21
8
TR
R L
TP
R L
R
15
15
5
TF
R L
R
Expanded roles of Lrp in transcription regulation
http://mgen.sgmjournals.org
Table 3. cont.
Table 3. cont.
Position
Microbial Genomics
936430
938542
946370
956734
985134
986550
1027954
1084060
1120372
1122552
1196730
1211242
1213450
1218154
1255430
1267356
1278770
1298670
1324836
1331770
1332958
1342734
1344942
1384666
1431960
1500460
1542070
1542844
1565340
1570272
1580646
1596458
1609970
1621964
1631434
1677572
1710570
1790134
1870038
1878844
1894766
2032166
Operon
aspC
ompF
hspQ
bssS
yceB
ymfD
iraM
bluR
ycgV
yciZ–deoT
gmr
pinR
narU
yddJ
dosCP
gadBC
ydeN
ydeK
yneF
dgcZ
cdgR
leuE
DB
Gene
Direction Lrp Direction Gene
Operon
ftsK
rarA
ycaD
ycaP
aspC
ompF
hspQ
efeB
bssS
yceB
ymfD
iraM
bluR
ycgG
ycgV
ychA
narK
ychE
yciQ
topA
cysB
yciZ
gmr
ycjF
pinR
tehB
narU
yddJ
dosC
gadB
ydeN
ydeK
yneF
dgcZ
ydfK
ydgH
nth
cdgR
yeaI
leuE
.
.
.
.
,
,
,
.
,
,
,
,
,
.
,
.
.
.
.
.
.
,
,
.
,
.
,
,
,
,
,
,
,
,
.
.
.
,
.
,
.
.
.
.
,
,
,
.
,
,
,
,
,
.
,
.
.
.
.
.
.
,
,
.
,
.
,
,
,
,
,
,
,
,
.
.
.
,
.
,
lolA
serS
ycaM
serC
ompF
asnS
yccW
phoH
dinI
grxB
ymfE
ycgX
ycgF
ymgF
ychF
kdsA
narG
oppA
rluB
cysB
ymiA
gmr
rnb
tyrR
ynaE
ydcL
yddJ
yddG
yddW
pqqL
ydeO
lsrK
yneG
ydeI
pinQ
ydgI
tppB
nlpC
yeaJ
yeaT
lolA–rarA
serS
ycaM
serC–aroA
nudL
rseX
.
.
.
.
sdaA
hchA
phoH
ymgF
kdsA
narGHJI
oppABCDF
rluB
cysB
ymiA–yciX
tyrR
ydcL
pinQ
ydgI–folM
tppB
yeaJ
sdaA
hchA
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Intensity L
76.4
112.2
34.7
122.3
45.3
14.0
28.3
68.3
218.8
23.3
24.1
60.7
14.1
18.0
51.3
13.3
11.8
44.0
10.0
37.6
22.1
418.9
77.8
55.6
236.6
10.3
30.9
340.4
58.8
306.3
81.0
21.8
43.9
23.9
311.1
177.3
210.9
13.7
11.1
301.1
88.3
462.6
ChIP
R L
AA
R L
TR
R L
TP
R L
TF
R L
R
T. Shimada and others
10
Type-B spacers
http://mgen.sgmjournals.org
Type-B spacers
11
Position
Operon
2054872
2064140
2083632
2165152
2173052
2202542
2210264
2231858
2249730
2267850
2301768
2311260
2327840
2403466
2414968
2663340
2729552
2735536
2802658
2882356
2920242
2925954
2989940
3023768
3048862
3056554
3098946
3117230
3119562
3134436
3183246
3265634
3359040
3383254
3416730
3437550
3444168
amn
cobU
yeeE
yegQ
gatABCD
gatA
yehK
yehS
yehS
yeiS
nfo
lpxT
yojO
micF
yfaQP
yfaQ
nuoABCEFGHIJKLMN nuoA
pta
yfhR
rrsG–gltW–rrlG–rrfG
rrsG
raiA
nrdF
casABCDE12
casA
gudPXD
gudP
ygdH
ygeG
ygfO
gcvTHP
gcvT
serA
serA
ansB
ansB
yghJ
yghJ
glcA
glcA
pitB
pitB
yqiC
tdcR
gltD
argR
yhdV
yhdN–zntR
yhdN
rplFR–rpsE–rpmD–
rplF
rplO–secY–rpmJ
yhhZ
livJ
livJ
yhhH
uspA
3581134
3597672
3622366
3638758
cobUST
yeeED
Gene
DB
Direction Lrp Direction Gene
Operon
.
,
,
.
,
.
,
.
.
.
.
.
,
,
.
.
,
.
.
,
,
.
.
.
,
,
,
,
,
,
.
.
.
.
.
,
,
.
,
,
.
,
.
,
.
.
.
.
.
,
,
.
.
,
.
.
,
,
.
.
.
,
,
,
,
,
,
.
.
.
.
.
,
,
yeeN
insH
yeeF
cyaR
gatZ
yehL
yehT
preT
yeiI
spr
eco
rcsD
yfaT
lrhA
yfcC
csiE
clpB
pheL
proV
cas3
yqcA
sdaC
ygeH
guaD
visC
rpiA
yggN
glcA
glcB
gsp
ygiL
yhaB
gltF
yhcN
yhdW
rplQ
rpsH
yeeN
.
,
.
.
.
,
.
.
yrhA
rpoH
yhhI
dtpB
cyaR
yehLMPQ
preTA
yeiI
spr
eco
rcsDB
yfcC
csiE
pheLA
proVWX
sdaCB
ygeH
guaD–ygfQ
ygiL
yhaBC
gltF
yhcN
yhdWXYZ
yrhA–insA–6AB–6B–6
yhhI
dtpB
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Intensity L
456.7
10.1
21.0
57.1
10.3
56.4
20.1
19.6
15.8
24.5
191.1
18.7
16.0
75.0
25.6
116.8
45.6
42.8
50.5
18.8
21.3
402.0
248.3
51.6
172.3
286.7
137.8
52.2
31.6
17.4
148.8
233.8
270.5
227.6
73.5
36.9
14.1
10.8
464.3
28.0
111.4
ChIP
R L
AA
R L
TR
R L
TP
R L
TF
R L
R
Expanded roles of Lrp in transcription regulation
Table 3. cont.
Table 3. cont.
Position
3649330
3672564
3676430
3706050
3737670
3752564
3755836
3790672
3794944
3851856
3886430
3886640
3913240
4042234
4076772
4213332
4220634
4257166
4292432
4304772
4336030
4346960
4352838
4358370
4381730
4411064
4427648
4497636
4523866
4540870
4609272
120 genes
Operon
yhjG
dppABCDF
yiaWV
yiaY
kbl–tdh
glmUS
arpA
yjcS
adiY
dcuB–fumB
lysU
cadBA
yjhIHG
64
Microbial Genomics
Total (type A+type B)
261 genes
142
296 targets
506 genes
DB
Gene
Direction Lrp Direction Gene
Operon
arsC
yhjD
yhjG
dppA
malS
yiaW
yiaY
kbl
rfaC
tisB
mnmE
tnaC
glmU
dsbA
yiiD
metA
arpA
dinF
nrfG
yjcS
adiY
dcuB
lysU
cadB
poxA
yjfM
fklB
insD
yjhI
fimE
prfC
.
.
,
,
.
,
,
,
.
.
.
.
,
.
.
.
,
.
.
,
,
,
,
,
.
.
.
.
,
.
.
yhiS
yhjE
.
.
,
,
.
,
,
,
.
.
.
.
,
.
.
.
,
.
.
,
,
,
,
,
.
.
.
.
,
.
.
yhiS
yhjE
yhjH
proK
avtA
aldB
selB
htrL
rfaL
emrD
tnaC
tnaA
atpC
yihF
yiiE
aceB
iclR
yjbJ
gltP
alsK
adiA
dcuR
yjdL
cadC
yjeM
yjfC
cycA
yjgW
sgcR
fimA
osmY
avtA
rfaL
emrD
tnaCAB
tnaAB
yihF
yiiE
aceBAK
yjbJ
gltP
yjeM
yjfC
cycA
yjgW
fimAICDFGH
osmY
Intensity L
ChIP
R L
AA
R L
TR
R L
TP
R L
TF
R L
56.3
373.5
22.5
442.5
96.6
98.0
13.2
111.5
372.6
389.0
24.5
29.3
28.0
41.1
19.4
50.0
11.2
40.0
217.5
11.2
12.3
70.7
61.6
12.1
24.4
13.1
398.4
11.1
47.1
83.3
374.9
76
126 genes
Operon
Gene
AA gene
15
53
34
55
107
80
34
68
68
8
17
17
42
63
27
9
9
3
154
245 genes
Operon
Gene
AA gene
53
53
53
87
180
150
54
114
114
12
25
25
55
84
35
24
24
8
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R
T. Shimada and others
12
Type-B spacers
Expanded roles of Lrp in transcription regulation
(Fig. 2, indicated in green colour; see Table S2 for the
entire list). Reduction of lrp mutant growth in the presence
of Ser agrees with the previous observation (Ambartsoumian et al., 1994). In contrast, growth of the lrp mutant
was slightly enhanced in the presence of dipeptides including Asp, Glu and Pro as a sole nitrogen source (Fig. 2,
shown in red and Table S2). These results suggested that
the function of Lrp was needed for utilization of some of
these specific amino acids as sole nitrogen sources. In the
simultaneous presence of NH4Cl, the addition of amino
acids did not affect growth of the lrp mutant (Fig. 2,
plate 5). One exception was the culture in the presence
of both NH4Cl and Leu, in which growth of the lrp
mutant was significantly reduced, indicating that excess
of Leu specifically interferes with cell growth in the absence
of Lrp.
PM2
PM1
Search for the physiological role of Lrp:
metabolome analysis
Results of the PM analysis indicated that the intracellular
composition of metabolites might be altered in the absence
of Lrp. To test this prediction, we next carried out the metabolome analysis using CE-TOF-MS. For the cells grown in
M9/glucose medium, a set of metabolites was measured
for both the WT and lrp mutant strains. The overall metabolite profiles indicated a considerable variation in the intracellular concentrations of not only amino acids, but also
some intermediate metabolites in the glycolysis/pentose
phosphate pathways and tricarboxylic acid cycle (Fig. 3;
for each metabolite see Fig. 4 and Table S3). The level of
Gly, Phe, Tyr and Trp was markedly higher in the lrp
mutant. In contrast, the level of Glu, Gln and Asp was
lower in the lrp mutant. The changes in amino acid levels
PM3
Cys
Ser
Trp
Ala
Gly
PM4
Ala–Gly Ala–Leu Gly–Asn
Ala–His Ala–Thr
PM5
Leu
PM6
Ala–Arg
Ala–Thr
Gly–Ala
Gly–Gly
Gly–Thr Gly–Arg
PM9
PM7
Ala–Asn
Arg–Ser
Ala–His
Gly–Lys
Gly–Met
Phe–Ser
Ser–Gly
Ser–Phe
Ser–His Ser–Met
Phe–Ala
PM8
Ser–Asn
Ser–Ser Thr–Ala
Gly–Ser Ser–Ala Thr–Gly
Trp–Ala Ser–Tyr Trp–Leu
Trp–Ser Tyr–Ala Trp–Arg Trp–Gly
Gly–Gly–Ile
Gly–Gly–Phe
Gly–Gly–Leu
Ala–Ala–Ala
PM10
pH9.5–Phe
Fig. 2. PM analysis of the Lrp mutant. PM analysis of E. coli WT BW25113 and its lrp mutant JW0872 was performed using the Biolog
PM apparatus according to the procedure provided by the provider. Growth patterns of microplates PM1–10 are shown: PM1 and 2, carbon source metabolism; PM3, nitrogen source metabolism; PM4, phosphorus and sulfur source metabolism; PM5, nutrient supplements;
PM6–8, peptide as nitrogen metabolism; PM9, osmotic and ion effects; PM10, pH effects. The curve of each well shows the time-course
(x-axis, up to 3 days) of cell growth as determined by measuring the amount of purple colour (y-axis) formed from tetrazolium dye
reduction. Data from the WT strain are shown in green, whilst data from the lrp mutant are shown in red. Yellow shows the overlap of the
two growth curves. Details are listed in Table S2.
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13
T. Shimada and others
Lrp (Tables 3 and S1) and thus the expression of a
number of genes involved in the metabolism of amino
acids should be indirectly regulated in the absence of Lrp,
leading to influence in the intracellular pool of respective
amino acids.
Metabolite level (lrp mutant/wild-type) (log2)
might be due to the regulation network of transcription factors for control of amino acid synthesis and utilization. For
instance, the highly accumulated aromatic amino acids are
all under the control of a single transcription factor, TyrR
(regulator of aromatic amino acid synthesis). Likewise, transcription factors of the genes for amino acid metabolism,
including AdiY and CysB (regulator of Cys synthesis),
LeuO (regulator of Leu synthesis), and TdcA and TdcR (regulator of Thr synthesis), are all under the direct control of
2.5
2
1.5
1
0.5
0
–0.5
–1
–1.5
–2
–2.5
2.5
2
1.5
1
0.5
0
–0.5
–1
–1.5
–2
–2.5
2.5
2
1.5
1
0.5
0
–0.5
–1
–1.5
–2
–2.5
a
The change in amino acid levels was interconnected with
the changes in the level of intermediate metabolites of
carbohydrate catabolism and energy metabolism. Some
specific amino acids showed a reverse correlation between
Amino acids
Trp 0.96
Gly 1.38
Phe 0.62
Ser –0.78
Ile –0.66
Pro –0.76
b
Arg –0.45
Asp –1.49
Gln –2.05
c
1
F1,6P -1.99
d
3PG+2PG–
0.31
PEP –0.40 R5P –0.59
2,3-DPG
–2.02
DHAP –2.20
Ru5P –1.28
-4
Malate
–0.10
Cis
Aconitate
-1.30
-2
-3
Fumarate
0.15
Citrate
0.25
-1
S7P –1.01
6–PG –0.93
TCA cycle
Succinate
–0.22
0
G6P –0.68
G1P –1.14
Glu –2.26
2
Glycolysis/PPP
F6P –0.41
Tyr 0.86
His 0.05
Met –0.06
Asn –0.13
Thr –1.03
Ala –1.15
Lys 0.28
Leu 0.12
Val –0.01
AcetylCoA
–4.43
-5
Nucleosides/nucleotides
Adenosine 1.06
Inosine 0.53
Cytosine 0.17
Guanosine 0.30
Adenine –0.94
IMP 1.39
GMP 0.19
ADP –0.20
AMP 0.17
Guanine –0.34
dTMP –0.06
ATP –0.71
dTDP –0.67
GDP –0.49
Hypoxanthine –0.68
CMP –1.20
UTP –0.82
GTP –0.93
CDP –1.20
CTP –1.36
dATP –0.86
dCTP –0.70
dTTP –1.15
Fig. 3. Difference of intermediate metabolites between WT and lrp mutant. E. coli WT BW25113 and its lrp mutant JW0872 were cultured in M9/0.2 % glucose medium until OD600 0.2 and all the intracellular metabolites were extracted as described in Methods. The
samples were subjected to CE-TOF-MS analysis according to the standard procedures as described in Methods. The intermediate
metabolites are classified into amino acids (a), intermediate metabolites of the glycolysis/pentose phosphate pathway (PPP) (b), metabolites in the tricarboxylic acid (TCA) cycle (c) and nucleosides/nucleotides (d). The ratio of metabolite levels between WT and the lrp
mutant (y-axis) is shown by log2.The level of difference of each metabolite is shown in Fig. 4 and details of the measurements are
described in Table S3.
14
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Microbial Genomics
Expanded roles of Lrp in transcription regulation
a
Ala
200
100
0
Leu
100
500
0
Lys
40
0
G1P
100
200
Phe
0
100
200
0
0
0
0
0
0
F6P
100
F1,6P
200
100
DHAP
0
0
R5P
S7P
100
50
40
50
0
200
200
0
0
Cyt
100
Ade
CMP
1000
50
0
100
0
GMP
10
Citrate
Gua
0
ADP
400
Ino
200
20
Ado
CCA
10
Guo
1000
500
10
0
0
0
Succinate
5
200
200
0
0
0
CDP
5000
ATP
2500
4000
dTMP
dTDP
Malate
0
CTP
2000
500
UTP
1000
0
200
500
6PG
250
1000
0
100
20
Fumarate
GTP
2000
0
100
PEP
1000
400
0
10
3PG+2PG
2000
400
100
0
0
20
GDP
200
500
0
40
50
20
0
20
Ace-CoA
1,3BPG
40
Val
200
0
0
400
Tyr
400
0
0
IMP
4
100
0
400
200
200
0
AMP
0
2
20
0
0
100
50
d
10
100
100
50
20
Trp
Ile
20
50
50
Ru5P
Thr
His
40
0
Ser
100
100
500
0
Pro
Gly
1000
2000
50
c
2
0
Glu
4000
50
G6P
200
200
Met
Gln
400
20
0
100
Asp
400
50
50
b
Asn
100
100
0
Concentration [pmol OD–1 (ml culture)–1]
Arg
200
400
Hpx
200
0
dCTP
400
0
dTTP
400
1
50
20
10
10
5
50
50
100
200
200
0
0
0
0
0
0
0
0
0
0
0
dATP
Fig. 4. Intracellular concentrations of major metabolites in WT and the lrp mutant. The intracellular concentrations of metabolites in WT
BW25113 (black bar) and its lrp mutant JW0872 (white bar) were determined by CE-TOF-MS. Major metabolisms that showed different
concentrations between the two strains are shown. Classification of the metabolites is as in Fig. 3.
the influence on cell growth and the intercellular concentration. In the presence of some dipeptides, such as Glu
and Pro, as a sole nitrogen source, the lrp mutant
showed a higher rate of cell growth than the WT cells.
The intracellular concentrations of Glu and Pro in the
lrp mutant were lower than those in WT (compare Figs 2
and 3). These growth and metabolic behaviours indicate
that effective availability of Glu and Pro in the lrp
mutant cells resulted in the promotion of growth. However, in the presence of some other dipeptides, such as
Gly and Trp, as a sole nitrogen source, the growth of the
lrp mutant was slower than the WT and their intracellular
concentrations were higher than the WT. The lower availability of these amino acids in the lrp mutant resulted in
growth retardation and accumulation of amino acids.
This reverse correlation implies that a group of amino
acids closely linked to the metabolic pathways for the production of metabolic energy is preferentially utilized for
the high growth rate of the lrp mutant, thereby showing
decreased levels of their intracellular pools.
http://mgen.sgmjournals.org
In the absence of Lrp, a marked change was also observed
in the intracellular composition of not only amino acids,
but also other metabolites (Fig. 3b–d). In particular, a
marked difference was detected in the level of acetylCoA, a major source of the metabolic energy, and the
key player in the degradation and synthesis of lipids and
amino acids. The level of acetyl-CoA in the lrp mutant
was 25-fold less than that in the WT cells (Fig. 4c).
Likewise, the level of dihydroxyacetone phosphate, 1,3bisphosphoglycerate, fructose 1,6-diphosphate, the intermediates of glycolysis, was lower in the lrp mutant
(Fig. 4b). The observed metabolic changes support the prediction of the coordinated linkage of carbon metabolism
with the alteration of amino acid metabolism. The reduction
of CMP, CDP, CTP, GTP and UTP (Figs 3 and 4) might lead
to the decrease in RNA synthesis in the lrp mutant.
Transcription regulation of the newly identified
targets by Lrp
Results of the SELEX-chip screening supported the concept
that Lrp is a global transcription regulator for the set of
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15
T. Shimada and others
Probe
WT Δ lrp
lysU
alaS
asnS
glyQ
In order to examine regulation in vivo of these aminoacyltRNA synthetase genes by Lrp, we performed Northern
blot analysis for detection of mRNA from these genes.
RNA samples were prepared from both E. coli WT
BW25113 and the lrp mutant JW0872, and subjected to
Northern blot analysis (Fig. 5). mRNA of lysU, the
known target of Lrp, was virtually undetectable in the
WT strain under the culture conditions employed, but a
high level of lysU mRNA was detected in the lrp mutant
strain, indicating strong repression of the lysU gene by
Lrp. Next, we analysed the level of mRNAs for seven
other aminoacyl-tRNA genes. The levels of serS, tyrS and
thrS were low in WT cells, but increased in the lrp
mutant, as in the case of lysU. mRNAs of other aminoacyl-tRNA genes were detected even in WT cells, but alaS
mRNAs increased, albeit at low levels, in mutant cells.
Thus, we concluded that Lrp participates in transcription
regulation of at least eight aminoacyl-tRNA synthetase
genes, of which expression of five aminoacyl-tRNA synthetase, including AlaRS, LysRS, SerRS, ThrRS and TyrRS, is
repressed by Lrp. So far only minimal Lrp-dependent
changes have been observed in the microarray analysis
(Tani et al., 2002), which was, however, carried out in
the cultures in the presence of Ile and Val addition.
In general, Northern blot analysis gives a more accurate
estimation of individual mRNA than microarray analysis.
serS
tyrS
glnS
thrS
rRNA
Fig. 5. Northern blot analysis of aminoacyl-tRNA synthetase
mRNAs. WT BW25113 and its lrp mutant JW0872 were grown
in M9/0.2 % glucose medium. Total RNA was prepared at the
exponential phase and directly subjected to Northern blot analysis under the standard conditions as described in Methods.
DIG-labelled hybridization probes are shown on the left side of
each panel. The amounts of total RNA analysed were calculated
by measuring the levels of 23S and 16S rRNAs stained with
methylene blue.
16
genes involved in transport, synthesis and degradation of
amino acids. The results of the PM assay and metabolome
analyses are both consistent with this concept. In addition,
Lrp was found to be involved in regulation of the genes for
the utilization of amino acids in the pathway of translation,
such as tRNA, tRNA aminoacylation, rRNA and ribosomal
proteins (Table 3; for details, see Table S1). E. coli carries a
total of 23 genes for aminoacyl-tRNA synthetase. Up to the
present time, regulation by Lrp has been recognized only
for the lysU gene that encodes lysyl-tRNA synthetase
(Gazeau et al., 1992), but no transcriptional regulators
have been identified for the other 22 aminoacyl-tRNA
synthetase genes [note that both GlyRS and PheRS are
composed of two different subunits, and E. coli contains
two forms (constitutive and inducible) of LysRS]. After
the Genomic SELEX screening, Lrp was found to bind
the promoter region of at least eight aminoacyl-tRNA
synthetase genes (alaS, asnS, glnS, glyQ, pheS, serS, thrS
and tyrS), implying the involvement of Lrp in transcription
regulation of these genes.
Discussion
Regulatory roles of Lrp
After SELEX-chip screening, at least 296 regulation targets
were identified for Lrp, resulting in an increase of *2.3fold. One group of the novel targets includes the genes for
utilization of amino acids such as the genes encoding
tRNA, aminoacyl-tRNA synthetase, rRNA and ribosomal
proteins. Here, a total of eight aminoacyl-tRNA synthetase genes were identified to be under the direct control
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Microbial Genomics
Expanded roles of Lrp in transcription regulation
of Lrp, but this number increases by setting the cut-off
level of SELEX pattern v10 (Fig. 1). In the case of
rRNA operons, all seven rRNA operons have been
reported to be under the control of Lrp (Pul et al.,
2005). In this study, only three were identified by setting
the cut-off level at 10, but all seven known rRNA operons
could be identified by setting the cut-off level at 3.0. The
whole set of regulation targets herein identified indicates
that Lrp senses the presence of nutritional conditions
and regulates not only the transport and metabolism
(synthesis and degradation) of amino acids, but also the
utilization amino acids up to protein synthesis. It should
be noted, however, that the selectivity of regulation targets
by Lrp should be altered after interaction of an effector
ligand.
Arg and Lys for ArgP (Marbaniang & Gowrishankar,
2011), glyoxylate and pyruvate for IclR (Lorca et al.,
2007), hypoxanthine and guanine for PurR (Houlberg &
Jensen, 1983), and uracil and thymine for RutR (Shimada
et al., 2007). Moreover, t activity control by more than
three effectors has been recognized recently for a set of
transcription factors such as CueR by Cu(II), Ag(II) and
Au(II) (Ibanez et al., 2013), TyrR by Tyr, Trp and Phe
(Pittard, 1996), and SdiA by three HSL analogues
(Shimada et al., 2013). In this respect, Lrp is unique
because its function is considered to be regulated at various levels by not only Leu, but also Ala, His, Ile, Met
and Thr (Hart & Blumenthal, 2011). The next step in the
research is to identify the whole set of regulation targets
of Lrp in the presence of each effector ligand.
E. coli contains as many as 300 species of transcription
factors, each monitoring a specific factor or condition in
the environment (Ishihama, 2010, 2012). The majority of
E. coli transcription factors belong to the one-component
signal transduction system, in which a single polypeptide
contains both an effector-binding sensory domain and a
DNA-binding domain. The activity of this group of transcription factors is controlled by a single species of the
effector ligand, i.e. inducer or co-repressor. In some
cases, the involvement of two effectors has been identified:
allantoin and glyoxalate for AllR (Hasegawa et al., 2008),
Hierarchy of the transcription factor network
involving Lrp
In the collection of a total of 296 Lrp targets selected
by SELEX-chip screening, a set of 21 transcription factor
genes was identified, including the lrp gene itself (Fig. 6).
Interestingly, the genes coding for local regulators of the
genes for individual amino acids are under the control of
Lrp, including AdiY (a regulator of Arg regulon), CysB (a
regulator of the Cys regulon), GadW (a regulator of Glu reg-
Lrp Network
YJ
AdiY
YhjI
Lrp
OmpR
BluR
Cbl
CadX
CadW
DctR
SdiA
GadE
GadW
GadX
DtcR
YbaO
CadX
CadW
CysB
YedW
SdiA
PhoP
DeoT
TyrR
H-NS
TdcR
EnvR
TdcA
TdcA
FabR
TdcA
StpA
GadW
SlyA
LeuO
LrhA
MatA
NanR
~20 TFs
FliE
LrhA
FlhDC
FliZ
MatA
FlhDC
QseB
FlhDC
Rob
LeuO
BglG
StpA
~10 TFs
QseCB
Fig. 6. Network of transcription factors (TFs) involving Lrp. After SELEX-chip screening, a total of 23 transcription factors were indicated
to be under the direct control of Lrp, altogether forming a big network, in which Lrp is located on the top of the hierarchy. In addition, the
genes encoding other transcription factors are organized downstream of some of these transcription factors.
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17
T. Shimada and others
ulon), LeuO (a regulator of Leu regulon), TdcA and TdcR
(regulators of the Thr and Ser regulons), and TyrR (a regulator of Tyr regulon) (Fig. 6, filled symbols). AdiY and GadW
are also involved in expression of the low pH response genes
for control of intracellular pH by using Arg and Glu, respectively (Ma et al., 2002; Stim-Herndon et al., 1996). LeuO is
another Leu-sensing global regulator that controls *140
targets, of which most are involved in anti-silencing against
the H-NS silencer (Shimada et al., 2011).
In addition to these amino acid-related transcription factors, Lrp was found to regulate a total of 15 transcription
factors (Fig. 6, grey symbols), which are involved in the
stress-response and life-style selection of E. coli, such as
GadW for acid response, YedW for copper and peroxide
response, EnvR for response to drugs, QseB for quorum
sensing, BluR for biofilm formation, and MatA and SlyA
for planktonic growth. Thus, the life style of E. coli under
these transcription factors is also under the control of
Lrp, which monitors the nutritional conditions in the
environment. Lrp is located upstream of this hierarchic
network including these two groups of transcription factors, thereby regulating a large number of genes indirectly
besides the total of *300 direct targets.
The authors acknowledge Ayako Kori and Kayoko Yamada of Hosei
University and Biomaterial Analysis Center, Technical Department of
Tokyo Institute of Technology for technical supports. This research
was supported by a Grant-in-Aid from the Institute for Fermentation,
Osaka and Grant-in-Aid for Young Scientists (B) (24710214) to T.S.,
and Ministry of Education, Culture, Sports, Science and Technology
of Japan (MEXT) Grants-in-Aid for Scientific Research (A)
(21241047), (B) (18310133) and (C) (25430173) to A.I., and the
MEXT-Supported Program for the Strategic Research Foundation at
Private Universities 2008–2014 (S0801037) and Network Joint Research
Center for Materials and Devices to T.S., N.S., M.M., A.I. and K.T.
Brinkman, A. B., Ettema, T. J. G., de Vos, W. M. & van der Oost, J.
(2003). The Lrp family of transcriptional regulators. Mol Microbiol
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Calvo, J. M. & Matthews, R. G. (1994). The leucine-responsive
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Chen, S. & Calvo, J. M. (2002). Leucine-induced dissociation of
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Chen, S., Hao, Z., Bieniek, E. & Calvo, J. M. (2001a). Modulation of
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Chen, S., Rosner, M. H. & Calvo, J. M. (2001b). Leucine-regulated self-
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